{"id":"W1941765526","doi":"10.1111/jvs.12323","title":"Effects of canopy composition and disturbance type on understorey plant assembly in boreal forests","year":2015,"lang":"en","type":"article","venue":"Journal of Vegetation Science","topic":"Ecology and Vegetation Dynamics Studies","field":"Environmental Science","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ministère des Ressources naturelles et des Forêts; Université Laval","funders":"Natural Sciences and Engineering Research Council of Canada; Fonds Québécois de la Recherche sur la Nature et les Technologies","keywords":"Understory; Canopy; Disturbance (geology); Deciduous; Ecology; Taiga; Species richness; Boreal; Abundance (ecology); Plant community; Environmental science; Biology; Geography","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006334716,0.00005276947,0.0001151722,0.0001067703,0.0000610512,0.00001103578,0.0001117777,0.00002338418,7.754102e-7],"category_scores_gemma":[0.0002073424,0.00004218648,0.00001244012,0.0003277668,0.0003656333,0.0003470014,0.00003026857,0.00008132235,0.000003622957],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000179926,"about_ca_system_score_gemma":0.00005925123,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002443516,"about_ca_topic_score_gemma":0.0002715817,"domain_scores_codex":[0.9992118,0.00004242641,0.0002069162,0.00009750724,0.000341109,0.0001001842],"domain_scores_gemma":[0.9994233,0.0001539722,0.0002474346,0.00004238686,0.00006263213,0.00007027282],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002105091,0.0001730416,0.9610016,0.00003046818,0.000007685629,0.00002578735,0.003107793,0.01701061,0.01461294,0.003064072,0.0001230025,0.0006324584],"study_design_scores_gemma":[0.0004753526,0.0004688669,0.9901493,0.00004987135,0.000006341537,0.00001602067,0.00007364192,0.0045689,0.00260325,0.001536938,0.000007152029,0.00004439164],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9977769,0.0001071397,0.0006133433,0.0001651918,0.0002163621,0.00006626752,3.369389e-7,0.000001857622,0.001052584],"genre_scores_gemma":[0.9992374,0.0000249194,0.0006424239,0.00007485326,0.000009034949,9.082081e-7,4.041985e-7,0.000001841301,0.000008168917],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02914764,"threshold_uncertainty_score":0.1720315,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0154403725270554,"score_gpt":0.267815230566963,"score_spread":0.2523748580399076,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}